You are absolutely correct. My apologies for not fully embracing the data-centric, process-driven paradigm from the start. Generating human-readable reports as the primary output is indeed a weakness if the goal is machine-readable documentation and structured interaction. Let's commit fully to the vision: **Templates define processes for the AI to execute, operating on a structured Project State Data, and interacting with the user primarily through structured questions.** This means most of the existing templates need to be fundamentally re-written from "Generate Document X" to "Execute Process Y, Update Project State, Ask Structured Questions." Here's a plan for the next level of improvement, focusing on this paradigm shift: **The Core Paradigm Shift:** * **Templates are Processes:** Each `.md` file is an instruction set for the AI to perform a specific *process* (e.g., `INITIATE-Project` is the process of setting up the project state, `EXECUTE-Task` is the process of performing work and updating task data). * **Project State is Central:** The AI maintains a single, structured data object (conceptually, could be YAML/JSON) representing the entire project's state (Charter data, Plan data, Task data, Logs, etc.). This is the primary "document." * **User Interaction is Structured:** The AI interacts with the user by presenting clear, often yes/no, questions or requests for specific, structured input (like providing the content of a source document). Freeform input is primarily for initial ideas or corrections, which the AI then parses into structured data. * **Outputs are Data or Structured Questions:** The primary outputs of executing a template are updates to the Project State data and the presentation of structured questions to the user. Human-readable summaries or full documents are generated *only when explicitly requested* as a specific task within the `EXECUTE-Task` process (e.g., "Execute Task: Generate Final Report"). **Plan for Improvement:** 1. **Define the Project State Schema:** Create a template (`DEFINE-ProjectStateSchema.md`) that explicitly outlines the structure of the central data object the AI will manage. This is the blueprint for the project's "memory." 2. **Convert Core Workflow (00-05) to Processes:** We've started this, but ensure they consistently: * Access/Update the Project State. * Formulate structured questions based on the *state* and the *process step*. * Handle user responses to update the state. * Propose transitions to the *next process* via structured questions. 3. **Convert Supporting Templates (`support/`) to Processes:** Redefine these templates to guide the AI in performing specific actions *on the Project State data* or using external inputs to *update* the state. * `DEFINE-*`: Processes to add/update definition data (Style Guide, Glossary, Metrics, Collaboration Guidelines) within the Project State. * `LOG-*`: Processes to add entries to log lists (Decisions, Insights) within the Project State. * `REVIEW-*`: Processes to analyze data within the Project State (e.g., analyze task data for performance, analyze feedback data) and update relevant statuses or generate summary data *within the state*. * `ANALYZE-*`: Processes to perform analysis on provided data or data within the state, and store the *results* of the analysis in the state. * `PLAN-Research_Extension.md`: Process to capture planning data for an extension and store it in the state (perhaps as a new project draft or a specific plan section). 4. **Convert Specialized Templates (`special/`) to Processes:** Redefine these as processes invoked *by* the `03-EXECUTE-Task.md` template for specific, complex tasks. * `GENERATE-*`: Processes to take inputs (potentially from the state) and generate specific output *data* (text, code, etc.), storing this output data in the state as a deliverable linked to the task. * `PROCESS-*` (CAFE cycles): These become complex processes that orchestrate sequences of steps, potentially invoking `EXECUTE-Task` or `ANALYZE-*` processes internally, and updating the Project State (especially the Framework State and Parameter Ledger data, which are part of the overall state). * `ANALYZE-*` (Specialized): Processes to perform specific analyses and store results in the state. * `EXTRACT-*`: Processes to extract structured data from unstructured input and store it in the state. 5. **Refine `03-EXECUTE-Task.md` as a Dispatcher:** Make `03-EXECUTE-Task.md` the primary template for *all* work execution. Its instructions will include: * Identifying the task from the Plan data. * Checking if the task requires a *specialized process* (e.g., "Draft Chapter 5" might require the `GENERATE-Academic_Manuscript` process). * If a specialized process is needed, the AI invokes *that process template* with the relevant task details and inputs. * If no specialized process is needed, the AI executes the task directly based on the DoD and instructions, updating the state. * In either case, `03-EXECUTE-Task` is responsible for updating the task status in the WBS and logging the output data. 6. **Create a User Guide:** Develop a `HOWTO-UseSystem.md` guide explaining this data-centric approach, how to start a project, how to invoke processes, how to interpret structured questions, and how the Project State data works. **Implications:** * **No More Markdown Reports (by Default):** The primary output of most template executions will be structured questions and internal state updates. Markdown reports are only generated when explicitly requested as a deliverable task. * **Centralized Data:** All project information lives in one conceptual data structure, improving context retention and analysis. * **Clearer AI Role:** The AI's instructions are focused on data manipulation and structured interaction. * **User Learning Curve:** The user needs to understand the concept of the Project State and how to interact via structured questions, but this should reduce the burden of managing multiple documents. This is a significant undertaking, requiring rewriting the core logic of most templates. But it directly addresses the verbosity and machine-readability issues you've highlighted and aligns with a truly data-driven collaborative AI system. Shall we proceed with redefining the templates based on this data-centric, process-driven model, starting with the `DEFINE-ProjectStateSchema.md`?